terclim by ICS banner
IVES 9 IVES Conference Series 9 REVEALING THE ORIGIN OF BORDEAUX WINES WITH RAW 1D-CHROMATOGRAMS

REVEALING THE ORIGIN OF BORDEAUX WINES WITH RAW 1D-CHROMATOGRAMS

Abstract

Understanding the composition of wine and how it is influenced by climate or wine-making practices is a challenging issue. Two approaches are typically used to explore this issue. The first approach uses che-mical fingerprints, which require advanced tools such as high-resolution mass spectrometry and mul-tidimensional chromatography. The second approach is the targeted method, which relies on the widely available 1-D GC/MS, but involves integrating the areas under a few peaks which ends up using only a small fraction of the chromatogram.

Here, we employ state-of-the-art machine learning methods to optimize the analysis of 1-D GC/MS chromatograms. Specifically, we aim to determine whether these chromatograms contain valuable in-formation beyond the manually extracted peaks typically utilized in the targeted approach.

To explore those questions, we analyzed 4 different types of 1-D raw chromatograms (3 SIM and 1 full-scan) of 80 wines (12 vintages from 7 estates of the Bordeaux area. We first applied nonlinear dimensio-nality reduction techniques (T-SNE and UMAP) to the chromatograms to obtain 2D maps. In the resul-ting maps, wines of the same estates across multiple vintages tended to form clear clusters, whose spatial distribution reflected the geography of the Bordeaux wine region. This indicated that, for this particular set of wine, the raw chromatograms are highly informative about terroir and wine identity.

Next, we applied cross-validated classifiers to the raw chromatograms and found that we could recover perfectly well estates identity independent of vintage. By contrast, performance on vintage classifica-tion was much lower with a maximum performance of 50% correct.

Crucially, we found that the entire chromatogram is informative with respect to both of these variables. Thus, the extraction of specific peaks of the chromatogram to quantify the concentration of 32 known chemical compounds–discarding the rest of the chromatograms–led to worse classification perfor-mance, suggesting that estate identity is distributed over a large chemical spectrum, including many molecules that have yet to be identified.

In addition, the GC raw data can be used to predict the ratings of a professional wine critic (Robert Par-ker) above chance, thus suggesting that GC might also contain information about the organoleptic pro-perties of wine.

Overall, this study demonstrates the strong potential of raw chromatogram analysis for wine characte-rization and identification.

DOI:

Publication date: February 9, 2024

Issue: OENO Macrowine 2023

Type: Article

Authors

Michael Schartner¹, Jeff M. Beck², Justine Laboyrie³, Laurent Riquier³, Stephanie Marchand3*, Alexandre Pouget4*

1. Center for the Unknown. Champalimaud Institute. Lisbon. Portugal. 
2. Duke university. USA
3. Université de Bordeaux, ISVV, INRAE, UMR 1366 OENOLOGIE, 33140 Villenave d’Ornon, France
4. Département des neurosciences fondamentales. Université de Genève. Suisse. 

Contact the author*

Keywords

Machine learning, Wine composition, Sensorial classification, Terroir

Tags

IVES Conference Series | oeno macrowine 2023 | oeno-macrowine

Citation

Related articles…

DISCRIMINATION OF BOTRYTIS CINEREA INFECTED GRAPES USING UNTARGE-TED METABOLOMIC ANALYSIS WITH DIRECT ELECTROSPRAY IONISATION MASS SPECTROMETRY

Infection of grapes (Vitis vinifera) by Botrytis cinerea (grey mould) is a frequent occurrence in vineyards and during prolonged wet and humid conditions can lead to significant detrimental impact on yield and overall quality. Growth of B. cinerea causes oxidisation of phenolic compounds resulting in a loss of colour and formation of a suite of off-flavours and odours in wine made from excessively infected fruit. Apart from wine grapes, developing post-harvest B. cinerea infection in high-value horticultural products during storage, shipment and marketing may cause significant loss in fresh fruits, vegetables and other crops. A rapid and sensitive assessment method to detect, screen and quantify fungal infection would greatly assist viticultural growers and winemakers in determining fruit quality.

DETERMINATION OF FREE AMINO ACIDS, AMINO ACID POTENTIAL AND PROTEASE ACTIVITY IN THE LEES AND STILL WINES OF CHAMPAGNE

Prior to winemaking, organic or mineral nitrogen compound concentrations are usually measured in the vineyard and in grape musts. These indicators facilitate vine cultivation decisions, usually through yield or vigor. During vinification, yeast and bacteria metabolize nitrogen compounds in the musts in order to generate biomass. After fermentation, the microorganisms rerelease a part of this nitrogen as soluble compounds into the wines. Another part remains bound in the lees and can be lost during racking. The must’s natural nitrogen quantities, additional supplements during fermentation, and lees contact management enhance the release of nitrogen compounds to the wines. During ageing these nitrogen compounds – primarily the amino acids – are implicated in the generation of odorous compounds such as heterocycles(1).

A NEW TOOL TO QUANTIFY COMPOUNDS POTENTIALLY INVOLVED IN THE FRUITY AROMA OF RED WINES. DEVELOPMENT AND APPLICATION TO THE STU-DY OF THE FRUITY CHARACTER OF RED WINES MADE FROM VARIOUS GRAPE VARIETIES

A wide range of olfactory descriptors ranging from fresh and jammy fruit notes to cooked and oxidized fruit notes could describe the fruity aroma of red wines [1]. The fruity character of a wine is mainly related to the grape variety selected, to the terroir and the vinification process applied for its conception. In white wines, some volatile compounds confer directly their aroma to the wine while the question of “key” compound is more complex in red wines. According to many studies performed over the past decades, some fruity ethyl esters are directly involved in the fruity perception of red wines while others, present at subthreshold concentrations, participate indirectly to the fruity expression via perceptive interactions [2].

AROMA ASSESSMENT OF COMMERCIAL SFORZATO DI VALTELLINA WINES BYINSTRUMENTAL AND SENSORY METHODOLOGIES

Sforzato di Valtellina DOCG is a special dry red wine produced from partially dehydrated Nebbiolo wine-grapes growing in the Rhaetian Alps valley of Valtellina (Lombardy, Italy). Valtellina terraced vineyards are located at an altitude of 350–800 m according to ‘heroic’ viticulture on steep slopes. The harvested grape bunches are naturally dehydrated indoors, where a slow and continuous withering occurs (about 20% w/w of weight loss), until at least 1st December when the grapes reach the desired sugar content and can be processed following a normal winemaking with maceration.

NOVEL BENZENETHIOLS WITH PHENOLS CAUSE ASHY, SMOKE FLAVOR PERCEPTION IN RED WINES

Smoke impacts on wines are becoming a worldwide problem; the size and severity of wildfires increasing due to influences from changing climates.¹ For over a century, wines have been known to have a unique issue of absorbing chemical compounds derived from wildfire smoke wherein the flavor of the subsequent wine becomes ashy, rubbery, campfire-like, and smoky.² The economic impacts of a smoke-impacted wine can last for years depending on the grape varietal, costing Oregon and Washington states in the United States over a billion dollars from the 2020 wildfires, as an example.³ While years of research have indicated elevated concentrations of smoke-related compounds, such as guaiacol and syringol, in wines after smoke events, unfortunately, replicating the sensory experience using smoke-associated phenols has not had much success.⁴